Effects of Heat Input in Laser Welding of Dissimilar Galvanized Steel to Aluminium Alloy
Bibliographic record
Abstract
The hybrid structures of aluminum-steel have been increasingly used for body-in-white constructions in order to reduce weight and cost.Obtaining acceptable joints between steel and aluminum required a better understanding of welding metallurgy and their effects on the resultant mechanical properties as well as the microstructure of the joints.In this research, laser welding of galvanized steel and aluminum alloy in an overlapped configuration was carried out.The influence of heat input on the weld bead dimension, microstructural and mechanical properties of the joints was studied.The experimental results showed that the penetration depth and weld width increased with the increase of heat input level.However, in order to limit IMC layer thickness and hardness at the surface of the weld seam and aluminum alloy, iron to aluminum dilution should be restricted by limiting the penetration depth.At lower heat input levels, less brittle IMC formation was formed.Consequently, with limited penetration depths at low heat input levels, tensile shear load increased, with failures located in the interface of the joints.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".